Smart Loads for Voltage Control in Distribution Networks

This paper shows that the smart loads could be effective in mitigating voltage problems caused by photovoltaic (PV) generation and electric vehicle (EV) charging in low voltage (LV) distribution networks. Limitations of the previously reported smart load configuration with only series reactive compensator (SLQ) (one converter) is highlighted in this paper. To overcome these limitations, an additional shunt converter is used in back-to-back (B2B) configuration to support the active power exchanged by the series converter, which increases the flexibility of the smart load without requiring any energy storage. Simulation results on a typical UK LV distribution network are presented to compare the effectiveness of a smart load with B2B converters (SLBC) against an SLQ in tackling under- and over-voltage problems caused by EVs or PV. It is shown that SLBCs can regulate the mains voltage more effectively than SLQs especially, under over-voltage condition. Although two converters are required for each SLBC, it is shown that the apparent power capacity of each converter is required to be significantly less than that of an equivalent SLQ.

The possibility of high Photovoltaic (PV) and Electric Vehicle (EV) penetration in Low-Voltage (LV) Distribution Networks (DN) is examined in this research utilising a typical DN found in Malta as a case study. The European Union (EU) has established goals and directives that make it quite probable that DNs will include a lot of PVs, causing overvoltages, and a lot of EVs, charging erratically, causing undervoltages. A DN may encounter both unfavourable scenarios on the same day since PV generation and EV charging often occurs simultaneously, particularly in residential case studies. Utilising dispersed or centralised storage effectively is one method to address these problems, however, doing so may postpone the need for costly DN expenditures. The paper demonstrates the level of automatic mitigation achieved in Malta residential areas. The information provided is mostly by actual measurements taken at the start of the LV feeder.

Over the last decade governments in Australia and around the globe have heavily promoted the installation of rooftop solar photovoltaics (PV) in residential low voltage (LV) distribution networks. While distributed solar PV offers a range of benefits, they have not significantly reduced distribution network demand during critical periods due to the incongruity between the residential load profile and the solar PV generation curve. The residential load profile has load demand in the morning, moderate demand during mid-morning, low demand during the middle of the day and peak demand in the evenings. In winter the mid-morning demand is greater than in summer leading to instances where there are two peak demand periods during the day. Solar PV generation is low during the morning and steadily increases until the middle of the day and then decreases until the evening. Peak solar PV generation typically occurs when demand in the network is low. This entails that solar PV resources are poorly utilised and high concentrations of solar PV generation in LV distribution networks can often lead to the degradation of power quality through overvoltage and instances of reverse power flow. Moreover, the addition of solar PV to existing LV networks with unbalanced phases can often exacerbate existing power quality issues in a particular overloaded phase. Corrective measures to address power quality issues may require costly augmentations to the electricity network.

As electric vehicles (EVs) uptake in the distribution networks continue to increase, it concerns distribution network operators (DNOs) that higher demand due to the charging of the EVs could undermine power quality (PQ) of their network. Of interest are challenges relating to undervoltage and thus the increase in electrical power losses. These challenges are exacerbated if EVs are charged uncoordinated. Therefore, in this paper, an optimized approach is proposed for the charging and discharging of EVs in a typical UK low-voltage distribution network with the goal to provide ancillary services to the DNOs. This is particularly in the context of voltage profile improvement and consequently electrical power loss minimization. The problem was formulated as a quadratic optimization task and solved using MATLAB. Results demonstrate that while uncoordinated charging could pose a challenge to the system operation, smart charge and discharge strategy of EVs can indeed offer power quality ancillary services (voltage profile improvement) to the system operator.

Scheduling the charging and discharging events of electric vehicles for quasi dynamic load flow calculations of a low-voltage distribution grid with regard to stochastic behavior and grid requirements

Electric vehicles (EV) have gained global attention due to increasing oil prices and rising concerns about transportation-related urban air pollution and climate change. While mass adoption of EVs has several economic and environmental benefits, large-scale deployment of EVs on the low-voltage (LV) urban distribution networks will also result in technical challenges. This paper proposes a simple and easy to implement single-phase EV charging coordination strategy with three-phase network supply, in which chargers connect EVs to the less loaded phase of their feeder at the beginning of the charging process. Hence, network unbalance is mitigated and, as a result, EV hosting capacity is increased. A new concept, called Maximum EV Hosting Capacity (HC max ) of low voltage distribution networks, is introduced to objectively assess and quantify the enhancement that the proposed phase-shifting strategy could bring to distribution networks. The resulting performance improvement has been demonstrated over three real UK residential networks through a comprehensive Monte Carlo simulation study using Matlab and OpenDSS tools. With the same EV penetration level, the under-voltage probability was reduced in the first network from 100% to 54% and in the second network from 100% to 48%. Furthermore, percentage voltage unbalance factors in the networks were successfully restored to their original values before any EV connection.

Clean energy incentives and the continuous fall in the cost of photovoltaic (PV) installations have led to a steady growth in residential PV systems. One of the main consequences of this high PV penetration in low voltage (LV) distribution networks is the overvoltage issue. Active power curtailment of PV inverters has been previously used to curtail the output power of the inverters below its operating point to prevent such overvoltages. This technique, however, uses a constant droop-based approach to curtail the power, based on the difference between the measured voltage and a critical voltage level. In this paper, this technique is implemented in a typical LV distribution network in North America with high PV penetration level. The simulation results show that the system undergoes excessive curtailment resulting in unnecessary energy loss. An adaptive droop-based approach using adaptive dynamic programming (ADP) is proposed as a possible solution to minimize the total energy loss in the system while keeping the system voltage under the critical operating limits. The energy loss due to curtailment has decreased by 25% after implementing the adaptive-droop based approach using ADP.

During the last few years, assessment and evaluation of power quality index due to large-scale penetration of electric vehicles in the system have gained significant attention. Voltage unbalance in the low voltage distribution network is amongst the main power quality issues caused by electric vehicles and therefore it has been quantified and analyzed in this paper. A CIGRE benchmark model of low voltage distribution network is taken as test network and simulations are performed on a sample urban power distribution network. An electric vehicle grid integration and its charging model is implemented in Simulink. Results for two charging strategies including uncontrolled charging and tariff based electric vehicle charging under different electric vehicle penetration levels and uneven charging scenarios have been obtained. The presented results show that an uneven EV charging scenario can cause significant voltage unbalance that goes beyond its allowed limit of 2 %.

Local control method and simulation analysis of hybrid AC/DC low-voltage distribution networks with high-proportion photovoltaics

A paradigm shift is taking place in Low Voltage (LV) distribution networks, motivated by progressive implementation of renewable micro-generation (µG), mainly Photovoltaic (PV), near household consumers. The concept of self-consumption linked to battery storage is emerging as a way to enhance the quality of electrical network. Smart-Grid (SG) environment comes close to this approach and may have a crucial relevance on management of intelligent power distribution networks, in the framework of a Smart Environment. This paper proposes an additional contribution on the subject by investigating the economic profitability of PV battery systems being analyzed with respect to its impact and economic feasibility, taking into consideration their initial investment and operation costs. The purpose is to verify if prosumer’s investment is financially more interesting than purchasing all electricity needed for consumption from the LV grid. The results of the performed economic analysis show that self-consumption with storage is a potential solution.

This study aims to quantity the impact of uncontrolled charging of Electric Vehicles (EVs) on the low voltage distribution networks with increasing EV penetration levels. For this objective, key indicators are developed to show the magnitude, scale and duration of the impact on the distribution network. The disseminated results are based on the case study with actual data from the existing distribution networks. The findings of this paper can serve as a benchmark for determining the potential of smart EV charging algorithms and/or the extent of necessary infrastructural reinforcement that the grid operators must incorporate.

While the number of the vehicle actuated with liquid fuels are settled, the count of electric vehicles is increasing. For the present moment most of them are scheduled for daily urban usage. This paper presents an analytical approach for estimation of the impact of electrical vehicle (EV) battery charging on the distribution grid. Based on the EV charge profile, load curve and local distributed generation the grid nodes, the time variation of grid parameters is obtained. A set of typical load profiles of EV charging modes is studied and presented. A software implementation and a 24h case study of low voltage distribution network with EV charging devices is presented in order to illustrate the approach and the impacts of EV charging on the grid. In the current paper an approach using variable nonlinear algebraic equations for dynamic time domain analysis of the charge of the electric vehicles is presented. Based on the results, the challenges due to EV charging in distribution networks including renewable energy sources are discussed. This approach is widely applicable for various EV charging and distributed energy resources studies considering control algorithms, grid stability analysis, smart grid power management and other power system analysis problems.

Grid-connected photovoltaic system in Malaysia: A review on voltage issues

The rapid increase of distributed energy resources (DERs) installation at residential and commercial levels can pose significant technical issues on the voltage levels and capacity of the network assets in distribution networks. Most of these issues occur in low-voltage distribution networks (LVDNs) or near customer premises. A lack of understanding of the networks and advanced planning approaches by distribution network providers (DNSPs) has led to rough estimations for maximum DERs penetration levels that LVDNs can accommodate. These issues might under- or over-estimate the actual hosting capacity of the LVDNs. Limited available data on LVDNs' capacity to host DERs makes planning, installing, and connecting new DERs problematic and complex. In addition, the lack of transparency in LVDN data and information leads to model simplifications, such as ignoring the phase imbalance. This can lead to grossly inaccurate results. The main aim of this paper is to enable the understanding of the true extent of local voltage excursions to allow more targeted investment, improve the network's reliability, enhance solar performance distribution, and increase photovoltaic (PV) penetration levels in LVDNs. Therefore, this paper reviews the state-of-the-art best practices in modeling unbalanced LVDNs as accurately as possible to avoid under- or over-estimation of the network's hosting capacity. In addition, several PV system modeling variations are reviewed, showing their limitations and merits as a trade-off between accuracy, computational burden, and data availability. Moreover, the unbalanced power flow representations, solving algorithms, and available tools are explained extensively by providing a comparative study between these tools and the ones most commonly used in Australia. This paper also presents an overview of unbalanced optimal power flow representations with their related objectives, solving algorithms, and tools.

The uncoordinated integration of electric vehicles (EVs) severely deteriorates the operational performance of a distribution network. To optimize distribution network performance in an EV charging environment, this paper presents a two-stage optimization approach, which integrates coordinated EV charging with network reconfiguration. A formulation to minimize system power loss is presented, and an optimal solution is obtained using a binary particle swarm optimization algorithm. The proposed approach is tested on a modified IEEE 33-bus medium-voltage node test system, coupled with a low voltage distribution network. Results of the coordinated and uncoordinated EV charging are compared with those of the developed integrated approach, and the operational performance of the system is studied. The results show that the integration of network reconfiguration with coordinated EV charging significantly decreases network power losses and fairly improves voltage profile. Thus, the proposed strategy can lead to improved operational performance of the system while dealing with the growing penetration of EVs in the network.